← Search

Jude Fernandes

2 accepted papers

2023

ROBBIE: Robust Bias Evaluation of Large Generative Language Models

EMNLP 2023long main

As generative large language models (LLMs) grow more performant and prevalent, we must develop comprehensive enough tools to measure and improve their fairness. Different prompt-based datasets can be used to measure social bias across multiple text domains and demographic axes, meaning that testing…

Cited by 0SourceScholar
2022

Perturbation Augmentation for Fairer NLP

EMNLP 2022main

Unwanted and often harmful social biases are becoming ever more salient in NLP research, affecting both models and datasets. In this work, we ask whether training on demographically perturbed data leads to fairer language models. We collect a large dataset of human annotated text perturbations and t…